Binarization plays an important role in document image processing, particularly in degraded document images. Among all local image thresholding algorithms, Sauvola has excellent binarization performance for degraded document images. However, this algorithm is computationally intensive and sensitive to the noises from the internal computational circuits. In this paper, we present a stochastic implementation of Sauvola algorithm. Our experimental results show that the stochastic implementation of Sauvola needs much less time and area and can tolerate more faults, while consuming less power in comparison with its conventional implementation.

Gastrointestinal (GI) discomforts are among the most common side effects of antiepileptic drugs (AEDs) that might lead to discontinuation or irregular consumption of the drugs. This study was conducted to evaluate the frequency of GI side effects of different AEDs in intractable epileptic patients treated with single or multiple drugs. GI discomfort of 100 epileptic patients (aged 35-76 years) treated with one or multiple AEDs was assessed. Seventy six patients (76%) were treated with two or more AEDs, and 24 (24%) were on monotherapy. The most common prescribed drug for monotherapy was carbamazepine and the most frequent combination was phenytoin and carbamazepine. Patients were suffering from different GI side effects including heartburn (34.6%), nausea (33.7%), constipation (26%), vomiting (22.1%), diarrhea (21.2%) and dysphagia (19.2%). Nausea and vomiting were significantly higher in patients receiving monotherapy with carbamazepine and valproic acid, respectively. When phenytoin, gabapentine, or valproic acid was added to the other AEDs, the risk of the occurrence of diarrhea, dysphagia, or heartburn was significantly increased, respectively. Addition of gabapentine to the other AEDs in multiple drug therapy was accompanied with the highest frequency of GI complications. This study indicated that GI side effects, which can affect drug absorption and utilization, were common in intractable epileptic patients with long-term AEDs treatment. This may influence the efficacy of the therapy with AEDs and enhance the probability of further attacks.

A soybean lecithin-based extender supplemented with hyaluronic acid (HA) was assayed for effectiveness to improve the quality of frozen-thawed ram semen. HA has not been tested yet in an extender containing soybean lecithin for freezing ram semen. Thus, the aim of this study was to analyse the effects of soybean lecithin at 1% or 1.5% along with HA at 0, 0.5 and 1 mg ml(-1) in a Tris-based extender on the motion characteristics, membrane integrity (HOST), viability, GSH peroxidase (GSH-PX) activity, lipid peroxidation and acrosomal status after freezing-thawing. Semen was collected from four Mehraban rams during the breeding season and frozen in the six lecithin×HA extenders. The extender containing 1.5% lecithin supplemented with no HA yielded higher total motility (52.5%±1.6), viability (55.8%±1.6) and membrane integrity (44.5%±1.7), but the effects of the lecithin concentration did not reach signification. Linearity-related parameters, ALH, BCF, lipid peroxidation, GSH-PX activity, morphology and acrosomal status were not affected by the extender composition. In general, adding HA significantly decreased sperm velocity (1 mg ml(-1) HA), total motility (only with 1.5% lecithin), viability (1 mg ml(-1) HA for 1% lecithin; both concentrations for 1.5% lecithin) and membrane integrity. In conclusion, adding HA to the freezing extender supplemented with soybean lecithin failed to improve quality-related variables in ram semen. Increasing the lecithin content could have a positive effect, but further studies are needed.

No abstract

Background: The aim of this study was to compare the clinical outcomes of applying Bio-OssÒ, an anorganic bovine bone xenograft (control group) to the combined use of Bio-OssÒ and Bio-GideÒ (a bioabsorbable collagen membrane) (test group) in human mandibular Class II furcation defects. Methods: A total of 18 furcations (8 tests and 10 controls) in 14 patients suffering from chronic periodontitis were treated in this randomized clinical trial. Open vertical and horizontal furcation depths (OVFD and OHFD), vertical and horizontal clinical attachment levels (VCAL, HCAL), probing depth (PD) and free gingival marginal level (GML) were among the clinical parameters measured prior and six months after treatment, at re-entry surgery. The data were analysed by statistical tests while a p value less than 0.05 was considered significant. Results: At the surgical re-entry, the mean reduction for OVFD of the control and test groups was 1.9 ± 1.3 and 2.1 ± 1.0, and for OHFD 2.1 ± 0.7 and 2.4 ± 1.3, respectively. The control and test treatments resulted in significant reductions in PD, VCAL and HCAL measurements at re-entry but there was no statistically significant difference between the two treatments in all soft and hard tissues measurements. Conclusions: This clinical trial failed to demonstrate the superiority of the combined use of Bio-GideÒ and Bio-OssÒ to the use of Bio-OssÒ alone, although both therapies resulted in significant gains in attachment level and bone fill.

Artificial neural networks are powerful computational systems with interconnected neurons. Generally, these networks have a very large number of computation nodes which forces the designer to use software-based implementations. However, the software based implementations are offline and not suitable for portable or real-time applications. Experiments show that compared with the software based implementations, FPGA-based systems can greatly speed up the computation time, making them suitable for real-time situations and portable applications. However, the FPGA implementation of neural networks with a large number of nodes is still a challenging task. In this paper, we exploit stochastic bit streams in the Restricted Boltzmann Machine (RBM) to implement the classification of the RBM handwritten digit recognition application completely on an FPGA. We use finite state machinebased (FSM) stochastic circuits to implement the required sigmoid function and use the novel stochastic computing approach to perform all large matrix multiplications. Experimental results show that the proposed stochastic architecture has much more potential for tolerating faults while requiring much less hardware compared to the currently un-implementable deterministic binary approach when the RBM consists of a large number of neurons. Exploiting the features of stochastic circuits, our implementation achieves much better performance than a software-based approach.

No abstract

Adenoid cystic carcinoma/basaloid cell carcinoma of the prostate (ACC/BCC) is a very rare variant of prostate cancer with uncertain behavior. Few cases are reported in the literature. Data on treatment options are scarce. The aim of our work was to retrospectively review the published reports. Thirty-three case reports or case series were analyzed (106 patients in total). Pathological features, management, and follow-up information were evaluated. Despite the relatively low level of evidence given the unavoidable lack of prospective trials for such a rare prostate tumor, the following considerations were made: prostate ACC/BCC is an aggressive tumor often presenting with locally advanced disease and incidental diagnosis occurs during transurethral resection of the prostate for urinary obstructive symptoms. Prostate-specific antigen was not a reliable marker for diagnosis nor follow-up. Adequate staging with Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI) should be performed before treatment and during follow-up, while there is no evidence for the use of Positron Emission Tomography (PET). Radical surgery with negative margins and possibly adjuvant radiotherapy appear to be the treatments of choice. The response to androgen deprivation therapy was poor. Currently, there is no evidence of the use of truly effective systemic therapies.